Scientific applications are still poorly served by contemporary relational database systems. At best, the system provides a bridge towards an external library using user-defined functions, explicit import/export facilities or linked-in Java/C# interpreters. Time has come to rectify this with SciQL, an SQL query language for scientific applications with arrays as first class citizens. It provides a seamless symbiosis of array-, set-, and sequence- interpretation using a clear separation of the mathematical object from its underlying implementation. A key innovation is to extend value- based grouping in SQL:2003 with structural grouping, i.e., fixed- sized and unbounded groups based on explicit relationships be- tween their dimension attributes. It leads to a generalization of window-based query processing with wide applicability in science domains. This paper is focused on the language features, extensively illustrated with examples of its intended use.

, ,
ACM New York, NY, USA
PlanetData , The SciLens Infrastructure for Data Intensive Research
Workshop on Array Databases
Database Architectures

Kersten, M., Zhang, Y., Ivanova, M., & Nes, N. (2011). SciQL, A Query Language for Science Applications. In Proceedings of EDBT/ICDT - Workshop on Array Databases 2011. ACM New York, NY, USA.